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OpenCV/tutoriel21/README.md

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+# Tutoriel OpenCV
+## Détection d'objet avec calcBackProject
+
+La vidéo du tutoriel est à l'adresse:
+https://www.youtube.com/watch?v=nMJertuuO08
+

OpenCV/tutoriel21/calcBackProject.py

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+import cv2
+import numpy as np
+from matplotlib import pyplot as plt
+
+nbr_classes=180
+seuil=30
+objet=0
+
+def click(event, x, y, flags, param):
+    global roi_hist, frame, objet
+    if event==cv2.EVENT_LBUTTONDBLCLK:
+        roi_x, roi_y, roi_w, roi_h=cv2.selectROI('ROI', frame, False, False)
+        roi=frame[roi_y: roi_y + roi_h, roi_x: roi_x + roi_w]
+        hsv_roi=cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
+        roi_hist=cv2.calcHist([hsv_roi], [0], None, [nbr_classes], [0, nbr_classes])
+        cv2.normalize(roi_hist, roi_hist, 0, 255, cv2.NORM_MINMAX)
+        cv2.destroyWindow('ROI')
+        plt.clf()
+        plt.plot(roi_hist)
+        plt.show(block=False)
+        plt.pause(0.01)
+        objet=1
+
+video=cv2.VideoCapture(0)
+cv2.namedWindow('Camera')
+cv2.setMouseCallback('Camera', click)
+while True:
+    ret, frame=video.read()
+    if ret is False:
+        quit()
+
+    if objet:
+        hsv=cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+        mask=cv2.calcBackProject([hsv], [0], roi_hist, [0, nbr_classes], 1)
+
+        _, mask2=cv2.threshold(mask, seuil, 255, cv2.THRESH_BINARY)
+        mask2=cv2.erode(mask2, None, iterations=3)
+        mask2=cv2.dilate(mask2, None, iterations=3)
+
+        cv2.imshow("Mask2", mask2)
+        image2=cv2.bitwise_and(frame, frame, mask=mask2)
+        cv2.imshow("Image2", image2)
+
+        elements=cv2.findContours(mask2, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
+        if len(elements) > 0:
+           c=max(elements, key=cv2.contourArea)
+           x,y,w,h=cv2.boundingRect(c)
+           cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 2)
+
+        cv2.imshow("Mask", mask)
+        cv2.putText(frame, "seuil[p|m]: {:d}".format(seuil), (10, 40), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 0), 1)
+
+    cv2.imshow("Camera", frame)
+    key=cv2.waitKey(1)
+    if key==ord('q'):
+        quit()
+    if key==ord('p'):
+        seuil=min(250, seuil+1)
+    if key==ord('m'):
+        seuil=max(1, seuil-1)
+
+video.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel21/calcBackProject2.py

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+import cv2
+import numpy as np
+from matplotlib import pyplot as plt
+
+objet=0
+nbr_classes=180
+seuil=30
+v1=0
+
+def click(event, x, y, flags, param):
+    global roi_hist, frame, objet
+    if event==cv2.EVENT_LBUTTONDBLCLK:
+        roi_x, roi_y, roi_w, roi_h=cv2.selectROI('ROI', frame, False, False)
+        roi=frame[roi_y: roi_y + roi_h, roi_x: roi_x + roi_w]
+        hsv_roi=cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
+        roi_hist=cv2.calcHist([hsv_roi], [0, 1], None, [nbr_classes, 256], [0, nbr_classes, 0, 256])
+        cv2.normalize(roi_hist[0, :], roi_hist[0, :], 0, 255, cv2.NORM_MINMAX)
+        cv2.normalize(roi_hist[1, :], roi_hist[1, :], 0, 255, cv2.NORM_MINMAX)
+        cv2.destroyWindow('ROI')
+        plt.clf()
+        plt.plot(roi_hist[0, :])
+        plt.plot(roi_hist[1, :])
+        plt.show(block=False)
+        plt.pause(0.01)
+        objet=1
+
+video=cv2.VideoCapture(0)
+cv2.namedWindow('Camera')
+cv2.setMouseCallback('Camera', click)
+while True:
+    ret, frame=video.read()
+    if ret is False:
+        quit()
+
+    if objet:
+        hsv=cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+        mask=cv2.calcBackProject([hsv], [0, 1], roi_hist, [0, nbr_classes, v1, 256], 1)
+
+        _, mask2=cv2.threshold(mask, seuil, 255, cv2.THRESH_BINARY)
+        mask2=cv2.erode(mask2, None, iterations=3)
+        mask2=cv2.dilate(mask2, None, iterations=5)
+
+        elements=cv2.findContours(mask2, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
+        if len(elements) > 0:
+           c=max(elements, key=cv2.contourArea)
+           x,y,w,h=cv2.boundingRect(c)
+           cv2.rectangle(frame, (x,y), (x+w,y+h), (0, 255, 0), 2)
+
+        cv2.imshow("Mask", mask)
+        cv2.imshow("Mask2", mask2)
+        image2=cv2.bitwise_and(frame, frame, mask=mask2)
+        cv2.imshow("Image2", image2)
+        cv2.putText(frame, "seuil[p|m]: {:d}  v1[o|l]: {:d}".format(seuil, v1), (10, 40), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 0), 1)
+
+    cv2.imshow("Camera", frame)
+    key=cv2.waitKey(5)
+    if key==ord('q'):
+        quit()
+    if key==ord('p'):
+        seuil=min(250, seuil+1)
+    if key==ord('m'):
+        seuil=max(1, seuil-1)
+    if key==ord('o'):
+        v1=min(250, v1+1)
+    if key==ord('l'):
+        v1=max(0, v1-1)
+
+video.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel21/histogramme.py

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+import cv2
+import numpy as np
+from matplotlib import pyplot as plt
+
+video=cv2.VideoCapture(0)
+mode=0
+nbr_classes=180
+
+while True:
+    ret, frame=video.read()
+    if ret is False:
+        quit()
+
+    if mode:
+        frame=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        hist=cv2.calcHist([frame], [0], None, [nbr_classes], [0, 256])
+        label="Intensité"
+    else:
+        hsv=cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+        hist=cv2.calcHist([hsv], [0], None, [nbr_classes], [0, 180])
+        label="Couleur"
+    cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX)
+
+    cv2.putText(frame, "Mode[o] {:d}  Nbr classes[p|m]: {:d}".format(mode, nbr_classes), (10, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
+    plt.clf()
+    plt.plot(hist)
+    plt.title(label)
+    plt.show(block=False)
+    cv2.imshow("image", frame)
+    plt.pause(0.001)
+
+    key=cv2.waitKey(5)&0xFF
+    if key==ord('q'):
+        quit()
+    if key==ord('o'):
+        mode=not mode
+        nbr_classes=(255 if mode else 180)
+    if key==ord('p'):
+        nbr_classes*=2
+    if key==ord('m'):
+        nbr_classes//=2
+
+video.release()
+cv2.destroyAllWindows()